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BBS301

Applying Mixed Methods Research to Business. A Big Data Focus.

Unit Information and Learning Guide version 1.3

TMA 2018

This information should be read in conjunction with the online learning materials

which can be found on your MyUnits page.

Unit coordinator

Name: Peter Batskos

School of Business and Governance

© Published by Murdoch University, Perth, Western Australia, December 2017.

This publication is copyright. Except as permitted by the Copyright Act no part of it may in any form or by any electronic, mechanical, photocopying, recording or any other means be reproduced, stored in a retrieval system or be broadcast or transmitted without the prior written permission of the publisher.

Information about the unit

Welcome to: BBS 301 Applying Mixed Methods Research to Business. A Big Data Approach.

Unit description

In this unit, students will explore basic philosophies relating to research design and analysis and begin to formulate focused, meaningful and feasible research ideas. The focus of the unit will be on Big Data. Data sources, data management and analytics will be explored from a commercial perspective.

Prerequisites

BBS200: Understanding Business Research: An Introductory Approach (previously BBS200: Business Research: An Integrated Approach

Aims of the unit

The broad aims of this unit are to:

• Provide an overview of the qualitative, quantitative and mixed methods approaches appropriate for research in Big Data.

• Provide an opportunity to gain practical experience in planning, conducting and communicating research projects.

Learning outcomes for the unit

On successful completion of the unit you should be able to:

1. Describe the main features of qualitative quantitative research methods

2. Use the SPSS statistical package to analysis big data

3. Generate a commercial standard Big Data segmentation project

4. Demonstrate a capacity to develop big data models using a combination of qualitative and quantitative techniques

5. Demonstrate a capacity to work collaboratively with team members including communication, project and time management skills

6. Demonstrate communications skills for presenting clear and coherent expositions of knowledge, ideas and evidence, both orally and in writing.

Graduate attributes developed in the unit

This unit will contribute to the development of the following Graduate Attributes.

Communication

Critical and creative thinking

Social interaction

Independent and lifelong learning

Ethics

Social justice

Global perspective

Interdisciplinarity

In-depth knowledge of a field of study

What you need to know

Generic information which students need to know is available at What you need to know web page.

The information includes:

• Assessment Policy

• determination of grades from components/marks

Contact details

Unit Coordinator’s contact details

Name: Peter Batskos

Email: p.batskos@murdoch.edu.au

Room: 301.009B (Building 440)

Phone: +618 93602170

Local Affiliate contact details

You will be notified who your local affiliate will be at the beginning of the teaching period. They will provide you with their contact details directly.

Administrative contact details

If you cannot get in touch with your unit coordinator, please contact:

School of Business and Governance

BGProgramSupport@murdoch.edu.au

How to study this unit

A blended learning approach is used in this unit, with online lectures plus two-hour workshops every week. You are expected to complete all pre-workshop activities, online lectures and essential readings provided before participating in the workshop each week. Workshops are a collaborative learning process and experience demonstrates they are most effective when students are prepared to participate. You are encouraged to access LMS weekly, to participate actively in online discussions, and to download any additional material where indicated. Post-workshop activities are focused on completing the semester-long Consultancy project, on which the assessment for this unit is based. For more information about blended learning see:

• • https://ift.tt/2M2qGgh
• • https://www.youtube.com/watch?v=xjYOajMCnkQ

Contact time and student time commitment

As this is a 3-credit point unit, we expect you to spend a minimum of 10 hours per week for the total weeks (15) of this teaching period (or 150 hours overall) working on this unit. Please refer to the study schedule for more detailed information about the weekly face-to-face contact time, online activities, readings and assessment details.

Attendance requirements

Internal students should attend as many of the workshops as possible. Workshops are designed to play an integral role in the progression of your Consultancy Project, and students should note that excellent grades in this unit are usually achieved by those students who engage fully and attend workshops regularly. You will be given time during workshops to work on your project under the supervision of your instructor.

For external students, you will also be placed in groups in the first Week of the semester. As external students are often studying in this mode for the flexibility it provides, a set online workshop time will not be specified. It is your responsibility to negotiate weekly meeting times, check-ins and deadlines with your group and record these activities in your group and individual activity logs.

All workshop activities will be provided to external students, and your tutor will be available to assist and advise you throughout the semester.

Please check the site carefully and see the Study Schedule to review session times and contact the unit coordinator if you have any queries.

Preparing for workshops

Preparation is required for all sessions. More information is available on the LMS site for each session. External students have the opportunity to engage in weekly online workshops.

Small group and interactive teaching and learning activities

Many of the learning activities in this unit will use small group discussions and group work. You will also be completing a group project as part of your assessment for this unit. Please see the learning guide and the LMS site for specific information about each session.

Unit changes in response to student feedback

Student feedback has informed a change in the assessments for this unit to focus on an applied research project with multiple parts. The learning activities in the unit are explicitly aligned with the focus on the applied research process assessment.

Resources for this unit

Essential Readings

Essential readings will be provided on LMS

Recommended textbooks

Blumberg. B., Cooper, D. and Schindler, S. (2014) Business Research Methods (4th ed.), Berkshire, England: McGraw-Hill.

(This text was used in BBS200 and provides an excellent overview of the methods and methodologies we will revisit in this unit. Use this text to refresh your basic knowledge of business research methods)

Creswell, J.W. (2014) Research Design (4th ed.), London: Sage Publications.

Easterby-Smith, M., Thorpe, R. and Jackson, P.R. (2015) Management and Business Research (5th ed.), London: Sage Publications.

Online resources

• • Special Interest Research Groups: o https://ift.tt/2LI3k3L
  • https://ift.tt/2KbpKol
  • https://ift.tt/2LIhLos

The following will be provided during the teaching period:

• • On line activities
  • Lecture slides
  • Lecture recordings
  • Electronic journal articles

Urkund

Your Unit Coordinators may use software called Urkund when viewing work that you submit.  Urkund is a pattern-matching system designed to compare work submitted by students with other sources from the internet, journals/periodicals, and previous submissions. Its primary purpose is to detect any submitted work that is not original and provide a thorough comparison between the submitted document and the original sources. Urkund will be replacing Turnitin (the previous pattern-matching software used by Murdoch) from 2016.

 

More information about how to avoid plagiarism is contained within the Murdoch Academic Passport (MAP) unit https://moodleprod.murdoch.edu.au/course/view.php?id=2684 .  University policies on academic integrity can be accessed here:  http://our.murdoch.edu.au/Educational-technologies/What-you-need-to-know/

Study schedule

Class	Session	Topic/Project/Study theme	Assessment items	Due
1	1.	Introduction
	2.	Philosophical foundations + mixed methods 1
2	3.	Mixed methods 2 – transforming
	4.	From words to numbers and content analysis
3	5.	Big data 4 Vs
	6.	Big data challenges – data aquisition
4	7.	Big data challenges – processes
	8.	Big data challenges -management
5	9.	Big data analytics 1 + SPSS clustering
	10.	Big data analytics 2 – make value with models
6	11.	Big data: adoption
	12.	Future of big data and where the high paid jobs are.
7		REVISION SESSION

Assessment

Assessment for this unit is conducted in accordance with the Assessment Policy.

Schedule of assessment items

You will be assessed on the basis of:

Assessment item	Description	Aligned Learning Outcomes	Value	Due
Assignment 1(Group)	Online survey of consumer attitudes to big data privacy and access issues (25%) + reflection paper on outcomes (5%)	1, 3	30%	Session 3
Assignment 2(Individual)	Big data in student’s major	2, 3, 4	30%	Session 5
Assignment 3 (Group)	Facebook data application	2, 4	40%	Session 7

Assessment details

Assignment 1 (30%, Group)

Groups for this assignment will be formed in session 1.

Groups of 3 to 4 students will produce an on-line survey (for example using Survey Monkey) to examine community attitudes to data privacy and access. The questionnaire should be brief, with no more than 10 questions. Lecturers/tutors will assist on the questions to ask. Groups may share ideas on questions, but each group must have a unique study.

This survey will have a “convenience” sample approach. Students should ask friends, work colleagues and family members to complete the survey. To get a spread of demographics, it is best not to use too many business students as respondents. The required minimum sample size is 50 completed surveys. It is therefore a semi-quantitative study – conclusions should reflect this.

Some starting ideas on questions include:

• I don’t like government departments having access to my personal details;

(1 strongly agree to 5 strongly disagree)

• I don’t like companies having access to my personal details;

(1 strongly agree to 5 strongly disagree)

• I don’t mind a government agency/company having access to my personal details if I get fast service or a good deal;

(1 strongly agree to 5 strongly disagree)

• I like browsing the web on my smart phone and finding a desired product that suits me.

(1 strongly agree to 5 strongly disagree)

Output required for assignment 1:

• An SPSS frequency table for each question in the survey;
• A copy of the questionnaire;
• The raw data file that has been downloaded from the on-line survey;
• A brief reflection paper (500 words) on the results. This reflection paper is worth 5% of the total – that is 5% of the 30%; and
• The components listed above should be compiled into I document.

Lecturers/tutors will assist groups with SPSS basics as required.

Marking Template Assignment 1

Criteria	Possible Mark
Quality of questionnaire and execution of survey	13
Presentation and correctness of SPSS tables	12
Reflection paper – clarity of writing	2
Reflection paper – ideas	3
Total	30

Assignment 2 (30%, Individual)

This is an individual project. The topic is:

“Discuss the opportunities and challenges of BIG DATA in the discipline of your major”

(Double major students can pick one or do both)

Output required:

• Essay style paper
• 2000 words
• 5-8 scholarly references (usually journal papers in the discipline of the major)
• 5-8 industry references (mainly industry magazines and specialist sites)

Marking Template Assignment 2

Criteria	Possible Mark
Standard of references	7
Incorporation of references into arguments	5
Arguments and ideas presented	12
Quality of writing	6
Total	30

Assignment 3 (40%, Group)

For this assignment, groups will be formed in Session 4. The groups should ideally comprise 3 to 4 members. All members of the group will receive the same mark for the assignment. The document submitted for marking will have the following parts:

• Objective(s);
• Method;
• Limitations;
• Segments developed;
• Products and services recommended for segments; and
• Appendices (to include SPSS cluster outputs, the excel data file, downloaded Facebook comments)

The approach for the assignment is detailed below.

Go to the Facebook site of the New York Times OR The Age

• Pick 5 -10 posts in any order.

• Select at least 300 comments in total from those posts.

• Copy and paste the comments into a word document – which must be attached as an appendix.

• Code (classify judgmentally) using the coding scheme given below.

• Enter your codes into an Excel data file with each comment being one record (row).

Facebook
Washington Post OR Sydney Morning Herald	Scales (1 to 7)
1.Clarity of ideas	1 clear ideas ………………………………………..…… 7 confused ideas
2. Level of emotion	1 low emotion ………………………………….……… 7 highly emotional
3. Level of objectivity	1 very objective ………………………………………… 7 very subjective
4. Past perspective	1 a lot of focus on the past ………………………… 7 no focus on the past
5. Now perspective	1 focus on now ………………………………………… 7 no focus on now
6. Future perspective	1 focus on the future ………………………………… 7 no focus on the future
7. Level focus on personalities	1 strong focus on people …………………… ……… 7 no focus on people
8. Level of criticism of corporates/business	1 highly critical of business ………………………… 7 no criticism of business
9. Level of criticism of the government/public service departments	1 highly critical of governments/public service …………… 7 no criticism of governments/public service

Example of coding

“I called my senators today concerning the war in Yemen to urge them to do what they can to stop our support of it. I intend to keep calling them. I know it’s not enough, though. We need a huge peace movement”	A comment from one post New York Times Facebook
	Rating using personal judgement
1.Clarity of ideas	2
2.Level of emotion	3
3.Level of objectivity	4
4.Past perspective	6
5.Now perspective	2
6.Future perspective	2
7.Level focus on personalities	3
8.Level of criticism of corporates/business	7
9.Level of criticism of the government/public service departments	1

Cluster analysis with SPSS

Basic cluster analysis from SPSS (sample data only)

Final Cluster Centres
	Cluster
	1	2	3
q1	3	3	2
q2	3	5	3
q3	2	3	2
q4	4	6	5
q5	5	1	2
q6	6	3	2
q7	2	4	4
q8	2	5	6
q9	3	5	6

Number of Cases in each Cluster
Cluster	1	140.000
	2	77.000
	3	73.000
Valid		290.000
Missing		.000

Psychographic segments

For example cluster 2 (that is; Psychographic segment 2) can be profiled in the following way:

• Focused on the now and the future
• Clear thinking and fairly objective

Possible segment 2 name: “Future Thinkers”

Products/articles/services each segment can be targeted with

Future thinkers: Books on climate change, electric cars, educational courses

Marking Template Assignment 3

Criteria	Possible Mark
Correct data downloading and data setup	5
Coding standard	15
Clustering quality	5
Segment development	5
Product recommendations	2
Report – format and clarity of writing	8

Examination

There is no final examination in this unit

Assignment submission

Use Chicago referencing style .

See the Murdoch library portal for citation style information.

All work is to be submitted in paper format. It is your responsibility to retain at least one electronic copy and one hard copy of the assignment before submission. This copy should remain in its original form as submitted and must be available for immediate submission if the original assignment is lost

Determination of the final grade

Your final grade in this unit is determined by combining the scores from all assessments to form a final grade. Therefore, it is not necessary to pass every assessable component to pass the unit. You must, however, receive a mark of at least 50% to pass the unit. Marks may be moderated to ensure equity of marking by different workshop facilitators on the same unit and/or to ensure consistency across examinations on different offerings of a unit and/or to ensure the same range of marks on the components of assessment.

Learning Guide

Class 1 Session 1 Introduction + SPSS essentials

Introduction

You will be placed in groups for assignment 1, introduced to the unit plus SPSS basics.

What you need to do

Before attending the workshop:

• Read the Unit Information and Learning Guide

• Read the essential readings

• Watch the recordings for the session

Learning outcomes

At the end of this session you will:

• Have an understanding of the unit structure
• Be able to load data into SPSS and perform basics functions

Resources for this topic

Essential readings (on LMS). SPSS in the computer las.

Learning activities/tasks

Discussion in groups: what do students understand by the term “Big Data”?

Students to practice bring data (say Excel) into SPSS and saving as a SPSS   Sav file. Students to label the valuables and labels and to run some frequency tables.

Explore on-line survey sites such as survey monkey.

Form groups of 3-4 people for Assignment 1

Class 1 Session 2 Philosophic foundations and mixed methods 1

Introduction

In this session, we will be exploring the philosophy of research and consider mixed method approaches.

What you need to do

Before attending the workshop:

• Watch the recordings for the session

Learning outcomes

At the end of this session you will:

• Understand the elements of a mixed methods design

• Choose a mixed methods design appropriate to the needs of a research project

Resources for this topic

Creswell reading, SPSS software

Learning activities/tasks

Compare the positivist and interpretive views on “plastic (non recyclable) shopping bags” – discuss in groups and report briefly to the class.

Set questions for on-line survey – in groups.

Discuss pros and cons of focus group research.

Class 2 Session 3 Mixed methods 2

Introduction

In this session, we will be looking at mixed methods research designs. We will learn how to identify mixed methods research and consider the indicators of quality in mixed methods research. 

What you need to do

Before attending the workshop:

• Watch the recordings for the session

Learning outcomes

At the end of this session you will:

• Understand the elements of a mixed methods design

• Choose a mixed methods design appropriate to the needs of a research project

Resources for this topic

Creswell reading, SPSS software

Learning activities/tasks

Discussion topic: In groups, suggest a mixed method approach for examining “What university students in your city think about (the positives and negatives) of globalisation” [this is a hot topic now with the US president Trump retreating from traditional economic trade agreements]  Present group ideas to the class considering issues such relative cost of doing the research, access to respondents etc.

Assignment 1 in lab if required

Class 2 Session 4: From words to numbers and content analysis

Introduction

In this session, we will be focusing on converting words to numbers for analysis, and content analysis in a big data context.

What you need to do

Before attending the workshop:

• Watch the recordings for the session

Learning outcomes

By the end of this session you will be able to:

• Have an understanding of content analysis methods

Resources for this topic

SPSS software

Learning activities/tasks

From any on-line news site, select 3 phrases, comments or words and classify them in terms of the SAO (Franzosi) model. Do in groups and share thoughts with the class.

Assignment lab work as required.

Class 3 Session 5: The 5 Vs of Big Data

Introduction

In this session, we will be looking big data: velocity, veracity, variety, value and volume.

What you need to do

Before attending the workshop:

• Read Gandomi and Haider required reading (on LMS)

• Watch the recording for the session

Learning outcomes

By the end of this session you will be able to:

• Understand the meaning of the 5Vs in terms of Big Data

• Provide examples of the 5V concepts

Resources for this topic

Gandomi and Haider required reading.

SPSS software.

Learning activities/tasks

Discussion question: In groups, give an example of each of the 5 Vs for – a big bank, an on-line retailer or an organisation suggested by the local lecturer.

SPSS lab work as required.

Class 3 Session 6: Big Data – Data acquisition issues

Introduction

This week we will consider some of the data acquisition issues that may arise before we start analysis

What you need to do

Before attending the workshop:

• Read Gandomi and Haider required reading (on LMS)

• Watch the recording for the session

Learning outcomes

By the end of this session you will be able to:

• Be aware of data sources for big data – public, internal, media

• Understand the differences between primary and secondary data

Resources for this topic

Labs for Facebook downloads (assignment 3)

Learning activities/tasks

Discussion question in groups: Select an organisation of interest to the group and list the sources of data that can be acquired – be specific. Share ideas with the class.

Start download of SMH or NYT Facebook data in labs, or continue process if group has already started.

Class 4 Session 7: Big Data challenges– processes

Introduction

In this session we will consider process options and related challenges.

What you need to do

Before attending the workshop:

• Review lecture slide ideas on aggregation

Learning outcomes

By the end of this session you will be able to:

• Aggregate on-line comments in a structured way

• Understand the importance of data cleaning

Resources for this topic

Labs and SPSS access.

Learning activities/tasks

Discussion question general class:  Why is data cleaning so important?

Discussion question group: Think of 6 aggregated categories for “likes” on Facebook – your friends. For example one aggregation  could be “likes for birthdays and other personal achievements”

Continue Assignment 3.

Class 4 Session 8: Management of data

Introduction

In this session we will look at managing data.

What you need to do

Before attending the workshop:

• Review Gandomi and Haider article

• Watch the recording 

Learning outcomes

By the end of this session you will be able to:

• Understand some of the key data management concepts

• Understand some of the difficulties involved in managing data

Resources for this topic

Labs and SPSS access.  Gandomi and Haider reading.

Learning activities/tasks

Questions for discussion.

1) Who owns social media data?  2) How can small organisation improve their data security?

Class 5 Session 9: Big Data Analytics, SPSS Clustering

Introduction

In this session, we will be looking at different analytics in a Big Data environment.

What you need to do

Before attending the workshop:

• Familiarize yourself with the SPSS, analyse, cluster screens

• Watch the recording

Learning outcomes

By the end of this session you will be able to:

• Understand the scope of Big Data analytics

• Develop your skills in SPSS clustering

Resources for this topic

Labs and SPSS access for Clustering.

Learning activities/tasks

Discussion questions:

1. What are some of the benefits and limitations of using Big Data scorecards?

2. Many analysts argue that “conversion” is the best on-line metric. Do you agree?

Practise SPSS clustering procedure.

Class 5 Session 10: Big Data analytics, creating value through models

Introduction

In this session, we will explore ideas on creating value for an organisation.

What you need to do

Before attending the workshop:

• Watch the recording

Learning outcomes

By the end of this session you will be able to:

• Understand the various model options possible in Big Data

• Identify opportunities for leveraging Big Data to create value for an organisation

Resources for this topic

Labs and SPSS access.

Learning activities/tasks

Discussion questions:

In groups, suggest a “leveraging” model for a company of the group’s choice. Discuss with class.

Analysis and profile development for assignment 3 continued.

Class 6 Session 11: Big Data: organisational adoption.

Introduction

In this session we will look at how companies may adopt Big Data.

What you need to do

Before attending the workshop:

• Watch the recording

Learning outcomes

By the end of this session you will be able to:

• Appreciate the importance of trust in the development of Big Data

Resources for this topic

There are no set readings or resources to for this session.

Learning activities/tasks

Discussion questions:

Work on assignment 3 profiles and product options.

Discussion question: Is trust more important than technology in Big Data?

Class 6 Session 12: Big Data: reflection + high paid, interesting jobs.

Introduction

In this session, we will review our ideas and consider various jobs in and around the Big Data world – analytical and non analytical.

Resources for this topic

There are no set readings or resources to for this session.

Learning activities/tasks

Discussion questions:

TBA by local lecturer

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